\begin{abstract}
Currently the problem of grouping patterns has been investigated from many different contexts and for many different researchers of diferent areas of research. This reflects its usability in  exploratory data analysis  which is used in many computing applications, both in its design and in the operators that generate them.
Procedures  of  data analysis can be divided into  explorers and  exploiters algorithms. This based on the ability of models and source input data . However conbinatory problems exists when generating clusters and  other problems that revolve around the context of the data to be analyzed. \\
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Natural computing is the  foundation  genesis of algorithms based on how nature acts to solve efficiently problems that are too complex. Many of which are used in artificial intelligence and { \em clustering } has been designed in this way. Among these are for example: neural networks \cite {colin}, swarm algorithm as ant colony systems \cite {baran},  bee colonies  systems  \cite {abbasa}, \ cite {abbasb}, genetic algorithms \cite{ozcan} , among others. \\
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So this work  propose the creation  of a new  { \em clustering } method . Having  the  actual theory of planet formation  from a primordial nebula that rotates around a star as inspiration. This is the  protosolar nebula theory now called \ac{SNDM}.
\end{abstract}
